Blute Blog

Blute's blog about evolutionary theory: biological, sociocultural and gene-culture.

Archive for December 2010

The evo-devo hour glass goes molecular but what explains it?

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In the nineteenth century the great German embryologist Karl Ernst von Baer proposed laws of embryological development – that general characteristics and structural relations develop before special ones; the form of an embryo does not converge on that of others but diverges from them; and that the embryo of a animal never resembles the adult of another animal but only its embryo. In modern language, embryological development is a process of differentiation in the senses that parts of an embryo become differentiated from each other and that members of different but related groups become more different from each other. Although Von Baer was not an evolutionist, Darwin thought that the early similarity of members of different groups was the best evidence for his theory of common descent. As he wrote in the Origin, “Community of embryonic structure reveals community of descent.” (Von Baer and the reception of his laws are discussed by Scott Gilbert here.)

While evolutionary changes in development themselves are presumably attributable to selection and/or drift, this pattern of change in development – less change earlier, more later – is most readily explained by constraints. A genetic mutation or recombination which affected the earliest stage of development would have more side effects down the road than would one which first acted later, and many of these would likely be maladaptive. Analogous phenomena are found in other selection processes. For example, a rat learning a maze with a series of choice points reinforced at the end eliminates mistakes in a backwards direction i.e. change takes place more readily in the later than in the earlier stages of the entire sequence. The philosopher of biology, William C. Wimsatt, dubbed the constraint principle in the evolution of development “generative entrenchment”.

In the 1990’s however, it turned out that the empirical generalization ‘more evolutionary change has taken place later than earlier in development’ does not quite hold – rather the difference between members of different but related groups resembles an hourglass (discussed for example by Raff in The Shape of Life). Groups differ more in the very earliest phase of development, converge to become more similar (the hour glass narrows to what is called the phylotypic stage in animals), and then diverge again quite a bit for the bulk of the rest of development. Kalinka et. al. writing in Nature (gated) have recently confirmed this hourglass pattern for gene transcription involved in key developmental processes by comparing six species of Drosophila.

I argued (in Darwinian Sociocultural Evolution pp. 146-8) that the constraints logic implies that the in-between phylotypic stage of minimal change/differences between groups must represent the actual historical origin of the taxa involved. This interpretation has now been borne out by Domazet-Lošo et. al. writing in the same issue of Nature. Using “phylostratigraphic” methods they had previously pioneered, they found from the transcriptome (all RNA molecules present), that the genes expressed in Zebra fish in the equivalent of the animal phylotypic stage are indeed older than those from other, including the earliest phase. They also confirmed this for some other groups using data from the literature.

But another question remains, again if the constraints logic is valid, how has so much evolutionary change in the earliest phase of development been possible? I argued that it must be because what appears to be the earliest phase of development is in actuality a later phase. Such would be the case if it were largely a maternal effect i.e. a later phase of the mother’s development. Intriguingly Domazet-Lošo et. al. did find significant differences between the age of genes expressed in the late juvenile and adult phases of males and females in Zebra fish with more newer in females than in males. The authors suggest this may be related to recent sexual selection (although it should be noted that Zebra fish are not notably sexually dimorphic and there is little evidence that female choice is more significant than male-male competition among them – if anything, the reverse may be the case). However, the sex difference is not really a test of the maternal effect hypothesis anyway because on my understanding (and I am not a molecular biologist) while maternally inherited RNAs would show up in the transcriptome, what would not show up would be if they were maternally inherited, or transcribed from maternally imprinted genes, or expressed as a consequence of maternally inherited protein transcription factors for example.

In short, I eagerly await whether the maternal effects hypothesis of ‘too much’ change early in development can and will be tested. If confirmed, Von Baer’s law would in a sense be restored.

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Written by Marion Blute

December 22, 2010 at 2:09 am

Necessity and invention

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In response to a query on a list serve, Geoffrey Hodgson with his usual exhaustive knowledge of the history of institutional economics, came up with a sought after quote from Thorstein Veblen, The Instinct of Workmanship (1914, p. 314):

“And here and now, as always and everywhere, invention is the mother of necessity.”

Exactly! Sociocultural evolution is Darwinian rather than Lamarckian.

In the first chapter of his lovely little book on The Evolution of Technology titled “Diversity, Necessity and Evolution”, George Basalla explains how the plethora of diversity in the made world can no more be explained by necessity than can the plethora of diversity in the natural world.

Written by Marion Blute

December 18, 2010 at 4:45 pm

Gene-culture coevolution and genomics

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Theorists have been talking about, modelling and providing anecdotal evidence for dual inheritance and gene-culture coevolution at least since the mid 1980’s (e.g. see Robert Boyd and Peter J. Richerson’s, Culture and the Evolutionary Process and William H. Durham’s Coevolution: Genes, Culture and Human Diversity respectively). A number of traits in particular populations have been plausibly linked to culture-driven genetic change including the effect of herding cultures on the level of expression of genes for lactose tolerance, of farming cultures on copy number expansion of genes for starch digestion, and of slash and burn agriculture on a gene conferring resistance to malaria but which can also result in sickle-cell disease for example. At a recent conference (the off-year meeting of the ISHPSSB), John Odling-Smee kindly drew my attention to two articles published this year which suggest that to bear greater scientific fruit, the multidisciplinary literature on gene-culture coevolution needs to be connected more closely with human population genomics (Laland et. al. gated, Richerson et. al. gated).

Human population genomics has already yielded a great deal of information about the relatedness and migration histories of various human populations. However, methods have also been developed for detecting recent (on the order of 100,000 years) strong positive selection on genes in human populations. Pickrell, in a blog post this year on Genomes Unzipped has simplified the explanation of these methods which are rich with acronyms in the literature. All identify alleles which have gone up in frequency unusually fast – either by identifying unusually large allele frequency differences between two populations or by finding young alleles at unusually high frequency within a population.

Some cautions are in order. First, the results of different statistical techniques used to infer this linkage disequilibrium can vary from identifying only hundreds to identifying thousands of genes subject to recent positive selection. A recent simulation study however has argued for the superiority of one of these (Huff et. al.). Secondly, culture could exert strong positive or negative selection pressures on genes to be sure, but with negative frequency-dependence among evolving cultural alternatives for example, it could also conceivably simply just leave alternative alleles in competition with each other (Blute gated). And last but not least, there is the question of the extent to which even recent strong selection necessarily implies a cultural cause.

Nevertheless, and this is the point of the post, Laland et. al. in their Table 2 (gated but reproduced below) have identified eight categories of genes from the literature, some including as many as 30 genes, whose function or phenotype is broadly known, and for which cultural selection pressures can reasonably be inferred.

As “next-generation” high-throughput sequencing technologies become available and cheaper (Metzker gated), although the major impetus for them is medical, they will inevitably ultimately be used to provide a denser set of sequences from more individuals in more populations yielding more information. In short, the traditional sociobiological story of genes-to-culture causal arrows by means of genes selecting among culturally transmitted alternatives is finally being supplemented on a large scale by a story of culture-to-genes causal arrows by means of culture selecting among genetically transmitted alternatives – all to the better of understanding both human unity and diversity.

  • Genes identified as having been subject to recent rapid selection and their inferred cultural selection pressures (Reproduced from Laland et. al. 2010)

Genes

Function or phenotype

Inferred cultural selection pressure

Refs

LCT, MAN2A1, SI, SLC27A4, PPARD, SLC25A20, NCOA1, LEPR, LEPR, ADAMTS19, ADAMTS20, APEH, PLAU, HDAC8, UBR1, USP26, SCP2, NKX2-2, AMY1, ADH, NPY1R, NPY5R

Digestion of milk and dairy products; metabolism of carbohydrates, starch, proteins, lipids and phosphates; alcohol metabolism

Dairy farming and milk usage; dietary preferences; alcohol consumption

6,7,16,41,63,102,118,144,145

Cytochrome P450 genes (CYP3A5, CYP2E1, CYP1A2 and CYP2D6)

Detoxification of plant secondary compounds

Domestication of plants

6,63,146,147

CD58, APOBEC3F, CD72, FCRL2, TSLP, RAG1, RAG2, CD226, IGJ, TJP1, VPS37C, CSF2, CCNT2, DEFB118, STAB1, SP1, ZAP70, BIRC6, CUGBP1, DLG3, HMGCR, STS, XRN2, ATRN, G6PD, TNFSF5, HbC, HbE, HbS, Duffy, α-globin

Immunity, pathogen response; resistance to malaria and other crowd diseases

Dispersal, agriculture, aggregation and subsequent exposure to new pathogens; farming

6,7,8,14,16,50,63,148,149

LEPR, PON1, RAPTOR, MAPK14, CD36, DSCR1, FABP2, SOD1, CETP, EGFR, NPPA, EPHX2, MAPK1, UCP3, LPA, MMRN1

Energy metabolism, hot or cold tolerance; heat-shock genes

Dispersal and subsequent exposure to novel climates

14,150

SLC24A5, SLC25A2, EDAR, EDA2R, SLC24A4, KITLG, TYR, 6p25.3, OCA2, MC1R, MYO5A, DTNBP1, TYRP1, RAB27A, MATP, MC2R, ATRN, TRPM1, SILV, KRTAPs, DCT

The externally visible phenotype (skin pigmentation, hair thickness, eye and hair colour, and freckles)

Dispersal and local adaptation and/or sexual selection

9,14,63,97,101,151

CDK5RAP2, CENPJ, GABRA4, PSEN1, SYT1, SLC6A4, SNTG1, GRM3, GRM1, GLRA2, OR4C13, OR2B6, RAPSN, ASPM, RNT1, SV2B, SKP1A, DAB1, APPBP2, APBA2, PCDH15, PHACTR1, ALG10, PREP, GPM6A, DGKI, ASPM, MCPH1, FOXP2

Nervous system, brain function and development; language skills and vocal learning

Complex cognition on which culture is reliant; social intelligence; language use and vocal learning

6,7,14,63,68,69,70,78,149

BMP3, BMPR2, BMP5, GDF5

Skeletal development

Dispersal and sexual selection

6,63

MYH16, ENAM

Jaw muscle fibres; tooth-enamel thickness

Invention of cooking; diet

80,113

Written by Marion Blute

December 8, 2010 at 2:56 am